Baltic Journal of Economic Studies 195 Vol. 11 No. 3, 2025 This is an Open Access article, distributed under the terms of the Creative Commons Attribution CC BY 4.0 1 University of Prishtina, Republic of Kosovo E-mail: arbana.sahiti@uni-pr.edu ORCID: https://orcid.org/0000-0002-9669-5913 2 University of Prishtina, Republic of Kosovo (corresponding author) E-mail: shqipdona.hashani@gmail.com ORCID: https://orcid.org/0000-0001-9807-0469 DOI: https://doi.org/10.30525/2256-0742/2025-11-3-195-202 THE CHOICE OF EXCHANGE RATE SYSTEMS, ACCOUNTABILITY IMPLICATIONS, AND ECONOMIC EFFICIENCY: EMPIRICAL EVIDENCE FROM DEVELOPING COUNTRIES Arbana Sahiti Ramushi1, Shqipdona Hashani Siqani2 Abstract. The choice of exchange rate regimes over the period 2000-2024 has been a key policy issue for developing countries. This paper will investigate the impact of different types of exchange rate regimes – fixed, intermediate and flexible – on economic growth performance. According to empirical data collected by the International Monetary Fund and the World Bank, the results are that there is no statistically significant relationship between the choice of exchange rate regime and the level of long-term economic growth. Descriptive data, on the other hand, show that countries that have followed intermediate regimes have experienced higher growth rates compared to fixed or flexible regimes. In this regard, central accountability implications arise: the way in which economic decision- makers report, explain and coordinate exchange rate policy is directly related to the perception of institutional credibility and the effectiveness of monetary and fiscal policies. Additionally, this study highlights the importance of accurate financial reporting and transparent accounting as essential elements for strengthening institutional accountability and creating a stable economic environment in developing countries. The findings show that the effects of exchange rates on economic development are not self-governing, but interdependent with other aspects such as trade openness, investment levels and institutional stability. Therefore, transparency and accountability in the design and implementation of monetary policies are key elements for the sustainable development of developing countries. Keywords: exchange rate, economic growth, exchange rate regimes, accountability, international trade, monetary policy. JEL Classification: F31, F43, O47, G15, M41 1. Introduction The exchange rate symbolizes the price of one country's currency in relation to the currency of another country. According to (Yagci, 2001) it is one of the most important factors in countries that apply open economies. The issue of exchange rate policies has become one of the biggest challenges of macroeconomic factors in developing countries after the collapse of the Bretton Woods system. In practice, these countries have applied different forms to manage the value of their currency in relation to other currencies, applying dollarization, currency boards, fixed exchange rates, exchange rates with exchange rate curves and controlled fluctuations. Even after the application of these methods, their impact remains unclear today (Ghosh et al., 1996). In an economy where the free movement of capital is implemented, according to (Eichengreen, 1998; Obstfeld & Rogoff, 1995) support the idea that only a fixed or flexible exchange rate is more stable. Although economic theories are supported by various studies where empirical evidence is divided. In practice, the implementation of these results is contradictory. The authors Edwards and Levy-Yeyati (2005), in their study support fiscal policy because according to them they bring more stability and credibility by affecting the reduction of inflation and stimulating economic growth. There are studies that support flexible policies with the argument that they give economies high flexibility to adapt to financial crises. According to the author Metinsoy (2024) Fixed exchange rate policies under the supervision of the IMF help stabilize economic crises, while Sussman and Baltic Journal of Economic Studies 196 Vol. 11 No. 3, 2025 Wyplosz (2024) in their study recommend that small countries benefit more from exchange rate flexibility. In their study, Yugay, Götz and Svanidze (2024) studied the importance of exchange rate policy on agricultural prices in Russia during the recent conflicts with Ukraine and concluded that the exchange rate plays a very important role in the production and services sectors of the economy. Similar results were also obtained by Born et al. (2024), emphasizing that exchange rate policy has a high efficiency in fiscal policies, as well as in the real sector of the economy. The economic crises caused by Southeast Asia (1997), Russia (1998) and Brazil (1999) have stimulated new debates on exchange rate policy issues, where in many empirical analyses unstable policies were identified as a key factor in economic crises (Domac et al., 2001). The affected countries, according to Calvo and Reinhart (2002), often use systems that are partially linked to the US dollar to create a flexible exchange rate. More recently, the conflict between Russia and Ukraine has again triggered a debate on the sustainability of exchange rate policy, which has shown that the exchange rate has an impact on economic stability and the real sector of the economy, which remains a key element for economies sensitive to international competition. This paper attempts to analyze the importance of Exchange Rate Policy (ERP) choices in the performance of developing country economies over the period 2000-2022. Applying the hybrid method of Bailliu et al. (2003). The main question of this study is: How do Exchange Rate Policies affect economic growth in developing countries? The main objectives are: • To analyze whether ERR has an effect on economic growth, based on other organizational factors. • To measure whether a fixed exchange rate policy has a positive effect by supporting trade openness. The paper analyzes 40 developing countries, which include three regions, America, Africa and Southeast Asia. This inclusion of regional countries helps us analyze the joint importance of exchange rates as a consequence of economic crises. The period covered by the study is 2000-2022. This period includes various financial crises starting from the Global Financial Crisis of 2008, the Eurozone Debt Crisis of 2010-2012, the outbreak of the COVID-19 pandemic of 2020-2021, as well as the consequences caused by the Russia-Ukraine conflict. These situations have given us an opportunity to analyze the effect of the ERR in preserving and promoting the long-term economy. 2. Literature Review The theories from different literatures, some support fixed policies and some support flexible policies. Mundell (1961) who studied the theory (Optimal Currency Area – OCA) recommends that for identifying exchange rate policies it is necessary to respect conditions such as trade friction, flexibility of buyers’ movement and characteristics of economic crises. Countries with a mature economy, as well as countries with an economy open to global trade, fixed policies are possible to assess prices and reduce advertising costs. Researchers Dornbusch (2001) and Barro & Gordon (1983) in their study have used fixed exchange rate policies in the formation of macroeconomic confidence and in reducing inflation, enabling other conditions for long-term investments. In contrast, Friedman (1953) and De Vita & Kyaw (2011) support the benefits of flexible exchange rate policies in terms of rapid adaptation to external attacks, as well as protection and internal adjustment of monetary policies. Harris and Rajgopal (2022) concluded that it is very important to present foreign exchange risks in accounting in accordance with international IFRS standards using financial instruments for hedging. They recommend that a good communication interaction can affect the reliability of financial statements and reduce the cost of capital, especially this is evident in developing countries where the sensitivity is very high to global shocks and financial systems that are less stable. Recent developments in the exchange rate literature contribute to emphasizing small changes in the classical literature, making the structural, organizational and political importance of the exchange rate clearer. In developing countries, accurate financial reporting and adherence to international accounting standards, such as IFRS, are critical for ensuring transparency and building institutional credibility (Harris & Rajgopal, 2022). Strengthening accounting practices improves the reliability of financial statements and reduces the cost of capital, which is essential for attracting foreign investment (Ball, 2006). Moreover, robust accounting systems enhance accountability in the management of public and private resources, supporting sustainable economic growth (Bushman & Landsman, 2010). Metinsoy (2024), in his study within the framework of IMF programs, concludes that flexible policies support these financial sectors by highlighting the various consequences in structural and social aspects. Sussman and Wyplosz (2024) have emphasized that political factors are important in the institutional capacity to determine exchange rate regimes, emphasizing that flexible exchange rate regimes are likely to be more successful in those institutions that have strong monetary currencies. Yugay and colleagues (2024) have pointed out that in situations of geopolitical uncertainty, flexible policies can exacerbate the situation of price volatility and increase the economy's exposure to external shocks. In the same vein, Dąbrowski et al. (2024) have suggested that the use of fixed policies is associated with Baltic Journal of Economic Studies 197 Vol. 11 No. 3, 2025 greater output volatility during crises, confirming the key role of the exchange rate in long-term economic stabilization. In the same article, Born et al. (2024) have highlighted the link between fiscal policies and exchange rate systems, showing that the effect of public spending on the real exchange rate and international competitive strength are closely related to exchange rate systems. New studies are trying to move from a rigid assessment to a more flexible and realistic approach where exchange rate regimes (ERRs) are not treated only as technical issues of monetary policy, but also as mechanisms with impacts that are integrated into macroeconomic, institutional and social dimensions. The choice of exchange rate regime is challenging and is closely linked to economic factors. No universal model is offered as the results are related to the level of impact from external shocks. 3. Methodology The scientific paper uses empirical analysis to develop and address the impact of the relationship between exchange rate variables and economic development of the countries that were taken for study. The study was conducted by considering panel data from 40 developing countries for the period 2000-2022. A wide range of variables that affect the efficiency of economic growth were used in the analysis. The macroeconomic model used is: GRi,t = αi+nt+Vi,t + β+ Xi,δ + єi, t (1) Where GRi,t is the growth rate of real GDP per capita in country i at time t, αi is a country-specific effect, ηt is a time-specific effect, Vi,t is a row vector of state variables, Xi,t is a row vector of growth determinants measured as averages over period t (29 control variables), and εi,t is an error term, β and δ are parameters to be estimated. The variables are measured on a five-year average. In this study, the Hausman test is used to address unexplained heterogeneity. And this test helps us see whether the model is fixed or random effects. Definition of Variables The selection of the control and state variables in this dissertation is informed by economic theory and literature. The dependent variable of the model is the growth rate of real per capita GDP, and the explanatory variables are: initial real per capita income, gross capital formation (investment), economic openness (imports plus exports as a percentage of GDP), proportion of those aged 25 and over who hold a secondary school qualification, money and quasi-money (M2), foreign direct investment (FDI), and an exchange rate regime dummy variable. All the variables are calculated as five-year averages during the observation period with the exception of the initial real per capita GDP and human capital proxy, which are measured at the beginning of each period. Table 1 is a brief explanation of the variables, anticipated signs of the coefficients, and the corresponding data sources. The analysis spans 40 emerging markets that traverse Latin America and Africa and Asia. Bailliu et al.'s (2001; 2003) hybrid classification method categorizes regimes as fixed and flexible according to their de facto operating features instead of official country reports. The first part of the empirical analysis uses the Ordinary Least Squares (OLS) regression to examine Table 1 Definition of variables, expected signs of coefficients and sources Variable Description Expected Sign Source GYP Real GDP per capita growth rate (% of GDP); dependent variable in the model. − World Bank, WDI GDP Real GDP per capita in natural logarithm, measured at the beginning of each period; represents initial conditions in the neoclassical growth model. − World Bank, WDI INV Total investment or gross capital formation (% of GDP); reflects capital accumulation. + World Bank, WDI E Average proportion of population over 25 years with secondary education; represents human capital. + Barro & Lee (2010) CON Real government consumption (% of GDP). − World Bank, WDI OP Trade openness indicator: the percentage of exports and imports of goods and services relative to GDP. + World Bank, WDI M2 Money and quasi-money (M2) as a percentage of GDP; indicator of financial sector development. + World Bank, WDI FDI Net foreign direct investment (% of GDP); measures international capital flows. + World Bank, WDI TRAFIX Interaction dummy for countries with greater access to international trade under fixed exchange rate regimes. ? Bailliu et al. (2001; 2003) ERD Dummy variable for the classification of exchange rate regimes (fixed, intermediate, flexible). ? Bailliu et al. (2001; 2003) Note: Variables are averaged over a five-year period for the period 2000–2022, except for GDP and E, which are measured at the beginning of each period Baltic Journal of Economic Studies 198 Vol. 11 No. 3, 2025 the effect of exchange rate regimes on economic growth. The estimation is carried out using the fixed effects model because of the potential endogeneity of exchange rate regime choice and the existence of unobserved country heterogeneity. The model accounts for problems of multicollinearity and cross-country heterogeneity. The results are tested for robustness by some other econometric techniques. Data is analyzed using the statistical package Stata offering high-end capabilities to handle panel data and test hypotheses in cross-country studies. 4. Results The initial assessment of the data explains the relationship between exchange rate systems and the impact of economic growth in developing countries. The data show that countries using intermediate systems have had average GDP growth rates per capita (1.99%) compared to those countries using neutral systems (1.80%) and fiscal systems (1.78%). To highlight the importance of extreme values, the median was examined and analyzed, which gave similar results and confirmed the advantage of intermediate systems. On the contrary, these analyses do not provide sufficient information to draw strong conclusions about the importance of non-intervention systems on economic growth. Therefore, it is very important to conduct a more detailed empirical analysis to assess whether there is statistical significance between the variables, taking into account other factors that have effects on the economic performance of these countries. Table 2 Average Growth rate of real per capita GDP (% of GDP) across Exchange Rate Regimes Exchange rate regimes Fixed Intermediate Floating ERR ERR ERR Growth rate of real per capita 1.78 1.99 2.00 GDP Mean Median 1.43 2.14 1.55 Source: Author’s calculate ERR classifications-HMR de facto from Bailliu et al (2000; 2003). Note: Based on 5-year average for the period 2000–2022 4.1. Pre-tests and Econometric Issues The study conducts pre-tests and econometric tests to validate the empirical estimates and establish the reliability of model results. The tests determine data stationarity and detect long-run connections between variables and protect against endogeneity and heterogeneity problems while choosing suitable estimation techniques. The tests serve as essential tools to guarantee that study conclusions rely on precise statistically valid results. 4.1.1. Estimation of Stationarity with the Unit Root Test To avoid possible errors resulting from the use of non-stationary data, the so-called "unit root test" was applied to verify whether these data are stationary or not. The use of this test is frequent because it helps in determining the models that we can use. Table 3 presents the results of all variables used in the regression, with the exception of artificial variables. Most of these results show that there is stability during the study period, with the exception of GDP per capita at the beginning. Since this variable was not constant at the beginning, in further analyses I used its change, which then shows stable results. Table 3 Unit Root Test Variabla Vlera GPY -6.2182** OP -4.8310** ED -5.8984** FDI -4.65671** INV -5.7772** CON -6.5838** GDP -3.9990 4.1.2. Engle-Granger Cointegration Test After the stationarity issues in panel data, the next step for assessment was to see if there is a long- run relationship between the variables through the cognitive test. The author Cameron (2005) emphasized that the presence of one or more cointegration vectors in the model underlines the acceptance of a stable causal relationship between the variables. So, to test this relationship, we used the Engle and Granger (1987) test on the model residuals. The results of this text are presented in Table 4. Table 4 Cointegration Test Variable Augmented Dickey-Fuller test (with a constant) RES -8.48** **5% significance level According to the results of the Engle-Granger cointegration test, the null hypothesis of no cointegration in the residuals gets rejected because the calculated t-value exceeds the critical asymptotic value of 2.862 (in absolute terms) at the 5% significance level from the McKinnon table. The results show that the regressors have cointegrated which means they maintain a long-term equilibrium relationship between variables and the level estimates remain consistent. 4.1.3. Granger Causality Test The results of the Granger causality test are presented in Table 5 using three lags to examine the growth rate Baltic Journal of Economic Studies 199 Vol. 11 No. 3, 2025 of GDP per capita (GDP) and other macroeconomic variables. The test results show that some variables exhibit significant causal relationships, while other variables do not exhibit statistically significant relationships. The test shows that GDP gives economic openness (Eo) at the 5% statistical significance level and an F value of 2.715. Statistical significance does not arise in the opposite direction of causality. There is a two-way causal relationship between GDP per capita growth and education level with a two-way effect between the variables. There is a reciprocal causality arising between GDP and the monetary aggregate M2 as the F value of 2.935 is higher than the statistical significance levels. The analysis shows that aggregate investment results in changes in GDP, but not in the opposite direction. The causality between GDP and other variables such as GDP, foreign direct investment (FDI), and public consumption (PCI) is statistically insignificant, as the values of the F statistics are not significantly different from zero. According to the analysis, GYP only shows causality to INV, but no other variables, including GYP-GDP and GYP-FDI and GYP-CO, show any causal relationship, because their F values remain statistically insignificant. The findings indicate that specific variables maintain bidirectional causal relationships, but other variables do not show causality, which may result from the model design and lag selection choices. To address a potential criticism of the growth regression regarding the failure to use annual data – which may reflect the short-term effects of changes in the exchange rate regime – the paper uses a cross- country regression using five-year averages of the control variables, in order to reflect the long-term relationship between the regimes and economic growth. The regression results are presented in Tables 6 and 7. Including 40 observed countries, R² values ranging from 0.40 to 0.56 indicate that the model explains about 40 to 56 percent of the variation in the data. The F-statistic values suggest that the regressions performed with the OLS method are statistically significant at the 5% level. Furthermore, to determine whether the most appropriate model is the fixed or random effects model, the Hausman specification test was applied, which rejected the null hypothesis of stable estimates under the random effects model (the p-value of the test is included in the baseline regression in Table 6). This implies that it is more appropriate to model the country effects as fixed effects. 4.2. Cross-country analysis of economic growth The main regression results are presented in Table 6. In general, the coefficients of the control variables are consistent with theoretical expectations and empirical findings, with the exception of the variable measuring economic openness. Starting from the basic factors, real growth per capita is positively related to human capital, measured by the percentage of the population over the age of 25 that has completed secondary education. This relationship is statistically significant and indicates that investment in education has a direct impact on economic growth in developing countries. Meanwhile, as the theory of conditional growth suggests, the first change in GDP per capita in the initial period results in a negative coefficient, indicating that countries with higher initial incomes tend to grow more slowly – that is, there is convergence. This result is also significant at the 5% level. In the case of economic openness, contrary to expectations, the effect is negative and not statistically significant. On the other hand, the investment to GDP ratio has a positive and significant impact, supporting the idea that investment plays a key role in stimulating growth. Similarly, foreign direct investment and financial sector development also have positive coefficients, but are not significant in this model. Another important finding is the negative impact of public spending on GDP per capita growth, which is statistically significant. Meanwhile, the dummy variable measuring the effect of exchange rate regimes has a negative coefficient, but is not statistically significant. This suggests that the exchange rate regime itself does not have any significant impact on the economic performance of developing countries, if all other factors are held constant. Another aim of this dissertation is to examine whether countries that have had more access to international trade during the analyzed period have experienced higher economic growth under fixed exchange rate regimes, as claimed by proponents of these regimes. For this purpose, a threshold of 65.32% has been set, which represents the average economic openness, and countries that exceed this level – considered as more open to global trade – have been selected. Table 5 Granger Causality test with 3 lags Relationship F-Statistic Interpretation GYP → GDP 0.798 No causality GDP → GYP 1.437 GYP → OP 2.715** Unidirectional OP → GYP 2.070 GYP → ED 4.640** Bidirectional ED → GYP 3.836** GYP → INV 0.708 No causality INV → GYP 0.875 GYP → FDI 2.398 Unidirectional FDI → GYP 5.045** GYP → M2 2.935** Bidirectional M2 → GYP 4.344** GYP → CON 0.984 No causality CON → GYP 2.047 Sours: Author Calulate: **indicates rejection of the null hypothesis at 5% level of significance Baltic Journal of Economic Studies 200 Vol. 11 No. 3, 2025 Table 6 Cross-country growth regression (Baseline) Variable Coefficient t-ratio Constant -1.624** (-2.285) DGDP -0.789** (-2.843) OP -0.004 (-0.857) ED 0.742** (2.757) INV 0.195** (6.712) FDI 0.150 (1.223) M2 0.0089 (0.745) CON -0.126** (-3.570) ERD -0.3534 (-1.293) Model Statistics R² 0.46 Hausman test (p-value) 0.003** Durbin-Watson test 1.66 F-statistic 18.22** Number of countries 40 Source: Author’s estimates. Note: Dependent Variable: Growth rate of real per capita GDP, t-ratios in parentheses. *, **, *** are significant at 10%, 5% and 1% level, respectively. All variables are computed on 5-year averages over the period 2000–2022 To measure these effects, a dummy interactive variable named TRAFIX has been used, which represents countries with more trade openness. Although its coefficient is positive, it is not statistically significant. The results for this analysis are presented in the section of Table 7 where all other variables have maintained the same values as in the basic regression. Table 7 Cross-country growth regressions Variable (i) HMR Coefficient (t-ratio) (ii) IMF Coefficient (t-ratio) Constant -0.966 (-0.557) -1.881** (-2.599) DGDP -0.958** (-2.577) -0.797** (-2.811) OP -0.003 (-0.773) -0.002 (-0.649) ED 0.084** (2.682) 0.067** (2.359) INV 0.172** (4.247) 0.195** (6.723) FDI 0.173 (1.111) 0.147 (1.200) M2 0.011 (0.963) 0.006 (0.596) CON -0.188** (-3.153) -0.118** (-3.343) TRAFIX 0.572 (0.438) – ERD -0.132 (-0.138) – IMF – 0.128 (0.547) Model Statistics (i) HMR (ii) IMF R² 0.56 0.44 Durbin-Watson Test 1.74 1.63 F-Statistic 9.00** 17.90** Number of Countries 15 40 Source: Author's estimates. Note: Dependent variable: Real GDP per capita growth rate, t-reports in brackets. *, **, *** are significant at the 10%, 5% and 1% level, respectively. All variables are calculated on 5-year averages over the period 2000–2022 Comparisons with other studies are difficult due to differences in countries and time periods, but our results are consistent with those of Ghosh et al. (1996) and Baxter and Stockman (1989), who found no significant correlation between exchange rate regime and economic growth. Other studies have confirmed different relationships, but according to a recent study by Abouelkhair and Tamsamani (2023), intermediate regimes such as managed flexibility and soft exchange rates are most suitable for growth in countries with high foreign trade and high foreign investment. But this study confirms the theory of monetary neutrality, according to which the exchange rate regime, being a nominal parameter, does not interfere with real growth in the long run. This idea has also been confirmed in previous studies (Fisher and Seater, 1993; Lucas, 1972), according to which nominal changes will not affect the real parameters of the economy in the long run. 5. Conclusions and Recommendations The aim of this study was to investigate the impact of exchange rate regimes on economic growth among developing countries, in light of the problems faced by the recent financial crises and the associated instability in the world economy. Evidence based on econometric models supports that fixed and flexible exchange rate regimes are not an important determinant of real economic growth over the period considered. Additional exploration of highly open countries with stationary regimes did not show a significant impact on economic growth compared to countries with flexible regimes. This result is consistent with the monetary neutrality hypothesis, which states that changes in nominal exchange rates will have no effect on real economic growth in the long run. Although descriptive statistics show that countries with intermediate regimes performed better, this result is not supported by statistically significant results. Here, the implication is that the choice of exchange rate regime does not have an autonomous and long-term impact on the economic growth of developing countries. Thus, macroeconomic policy design should place greater emphasis on structural and institutional factors that favor long-term growth. One of the key areas that emerges from this perspective is the role of accountability in accounting, which should be used in an effort to deepen transparency and credibility in economic management. In general, developing countries need to establish strong accounting capacities and clear financial reporting systems, as dictated by international standards, so that they can bring about greater institutional accountability and efficiency in the use of resources. A strong accountability system supports the creation of a stable investment environment and Baltic Journal of Economic Studies 201 Vol. 11 No. 3, 2025 improves the ability of countries to cope with crises and to encourage sustainable growth. Recommendations from the paper's analysis: • Effects of exchange rate policy: None of the exchange rate policy choices has any major effect on long-term economic growth. Macroeconomic policy in developing countries should prioritize price and political stability, and not encourage further exchange rate manipulation. • Building institutional effectiveness. Developing countries need to build institutional structures that will ensure economic performance in appropriate actions and strengthen the credibility of macro- economic policies. • The indirect importance of exchange rate systems Exchange rate systems can be applied indirectly to economic development by improving the conditions for international trade, investment, and the development of financial institutions. • Macroeconomic policy flexibility. Developing countries need to maintain macroeconomic policy flexibility in order to cope with external policy shocks and economic crises, as these can hinder the economy's flexibility to new conditions. • Improving accounting systems. Improving and modernizing accounting capacities in developing economies, through harmonization of international standards and strengthening the quality of transparent financial reporting, which plays a key role in economic analysis and evidence- based policymaking. • Need for further research. The relationship between exchange rate regime and economic growth remains complex and unclear, requiring further research with more advanced methods and in-depth empirical approaches to reach clearer and more consistent conclusions. The main purpose of these recommendations is to help develop more effective and sustainable macroeconomic policies for developing countries, thereby contributing to improving their long-term economic performance. References: Abouelkhair, A., & Tamsamani, Y. (2023). Exchange rate regime choice and economic growth: An empirical analysis on African panel data. African Review of Economics and Finance, 15(1), 18–35. Bailliu, J., Lafrance, R., & Perrault, J. F. (2001). Exchange rate regimes and economic growth in emerging markets. In Revisiting the Case for Flexible Exchange Rates (pp. 317–345). Bank of Canada. Bailliu, J., Lafrance, R., & Perrault, J. F. (2003). Does exchange rate policy matter for growth? International Finance, 6(3), 381–414. 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DOI: https://doi.org/10.1111/agec.12720 Received on: 17th of May, 2025 Accepted on: 04th of July, 2025 Published on: 24th of July, 2025